Understanding and overcoming obstacles in adaptive management
Authors: Johan Månsson, Louise Eriksson, Isla Hodgson, Johan Elmberg, Nils Bunnefeld, Rebecca Hessel, Maria Johansson, Niklas Liljebäck, Lovisa Nilsson, Camilla Olsson, Tomas Pärt, Camilla Sandström, Ingunn Tombre, Steve M. Redpath
Journal: Trends in Ecology & Evolution (2022)

Adaptive management (AM) is a stepwise iterative process in which interventions are implemented, their effects monitored and evaluated, and the next intervention adapted according to knowledge gained.In theory, this process of learning and adaptation leads to increased understanding of ecological processes and improved management. However, the AM approach faces many obstacles to its effective implementation.These obstacles may be exacerbated by emerging challenges related to a rapidly changing environment. In the face of large-scale climate and land use change, AM's stepwise learning may not keep pace with environmental changes.To inform future AM schemes, a transdisciplinary approach is needed to address obstacles in technical and social components of AM, but also obstacles related to the ecosystem and governance system. Adaptive management (AM) is widely promoted to improve management of natural resources, yet its implementation is challenging. We show that obstacles to the implementation of AM are related not only to the AM process per se but also to external factors such as ecosystem properties and governance systems. To overcome obstacles, there is a need to build capacities within the AM process by ensuring adequate resources, management tools, collaboration, and learning. Additionally, building capacities in the legal and institutional frames can enable the necessary flexibility in the governance system. Furthermore, in systems experiencing profound changes in wildlife populations, building such capacities may be even more critical as more flexibility will be needed to cope with increased uncertainty and changed environmental conditions. Adaptive management (AM) is widely promoted to improve management of natural resources, yet its implementation is challenging. We show that obstacles to the implementation of AM are related not only to the AM process per se but also to external factors such as ecosystem properties and governance systems. To overcome obstacles, there is a need to build capacities within the AM process by ensuring adequate resources, management tools, collaboration, and learning. Additionally, building capacities in the legal and institutional frames can enable the necessary flexibility in the governance system. Furthermore, in systems experiencing profound changes in wildlife populations, building such capacities may be even more critical as more flexibility will be needed to cope with increased uncertainty and changed environmental conditions. For decades, AM (see Glossary) has been widely touted as an approach to decision-making capable of handling complexities and uncertainties when managing natural resources [1.Holling C.S. Adaptive Environmental Assessment and Management. John Wiley & Sons, 1978Google Scholar, 2.Walters C.J. Holling C.S. Large-scale management experiments and learning by doing.Ecology. 1990; 71: 2060-2068Crossref Scopus (1030) Google Scholar, 3.Allen C.R. Gunderson L.H. Pathology and failure in the design and implementation of adaptive management.J. Environ. Manag. 2011; 92: 1379-1384Crossref PubMed Scopus (221) Google Scholar, 4.Westgate M.J. et al.Adaptive management of biological systems: a review.Biol. Conserv. 2013; 158: 128-139Crossref Scopus (259) Google Scholar]. AM is a stepwise process of learning and adaptation, using structured decision-making to reach management goals [5.Johansson J. et al.Inspired by structured decision making: a collaborative approach to the governance of multiple forest values.Ecol. Soc. 2018; 23: 1-11Crossref Scopus (9) Google Scholar, 6.Bunnefeld N. et al.Decision-making in Conservation and Natural Resource Management: Models for Interdisciplinary Approaches. Cambridge University Press, 2017Crossref Google Scholar, 7.Williams B.K. et al.Adaptive management: The U.S. Department of the Interior Technical Guide. U.S. Dept. of the Interior, Adaptive Management Working Group, 2009Google Scholar]. Often referred to as a 'loop', AM involves the iteration of several stages, including set-up (framing of the problem and identification of objectives, hypotheses, and management actions), implementation, monitoring, and evaluation (Figure 1). Based on the knowledge gained from the latter stages, original goals and interventions are reviewed and adjusted if necessary, and a new 'AM loop' ensues [1.Holling C.S. Adaptive Environmental Assessment and Management. John Wiley & Sons, 1978Google Scholar,6.Bunnefeld N. et al.Decision-making in Conservation and Natural Resource Management: Models for Interdisciplinary Approaches. Cambridge University Press, 2017Crossref Google Scholar,7.Williams B.K. et al.Adaptive management: The U.S. Department of the Interior Technical Guide. U.S. Dept. of the Interior, Adaptive Management Working Group, 2009Google Scholar]. This stepwise and structured process of 'learning by doing' [2.Walters C.J. Holling C.S. Large-scale management experiments and learning by doing.Ecology. 1990; 71: 2060-2068Crossref Scopus (1030) Google Scholar] is assumed to lead to improved understanding of the system and thereby an ability to design more effective interventions to fulfil objectives. AM is widely promoted in both the scientific literature [4.Westgate M.J. et al.Adaptive management of biological systems: a review.Biol. Conserv. 2013; 158: 128-139Crossref Scopus (259) Google Scholar,8.Perino A. et al.Biodiversity post-2020: closing the gap between global targets and national-level implementation.Conserv. 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Conserv. 2013; 158: 128-139Crossref Scopus (259) Google Scholar], and it has been implemented to manage slow as well as rapid changes in resource availability [4.Westgate M.J. et al.Adaptive management of biological systems: a review.Biol. Conserv. 2013; 158: 128-139Crossref Scopus (259) Google Scholar,11.Marjakangas A. et al.International Single Species Action Plan for the Conservation of the Taiga Bean Goose (Technical series No. 56), AEWA, Bonn, Germany.2015Google Scholar,12.Madsen J. et al.Implementation of the first adaptive management plan for a European migratory waterbird population: the case of the Svalbard pink-footed goose Anser brachyrhynchus.Ambio. 2017; 462: 275-289Crossref Scopus (68) Google Scholar]. When it comes to wildlife populations, AM has been applied on spatial scales ranging from local to biome [13.Cummings J. et al.Adaptive restoration of sand-mined areas for biological conservation.J. Appl. Ecol. 2005; 42: 160-170Crossref Scopus (34) Google Scholar,14.Nichols J.D. et al.Adaptive harvest management of North American waterfowl populations: a brief history and future prospects.J. Ornithol. 2007; 148: 343-349Crossref Scopus (188) Google Scholar]. Despite the wide range of actors advocating AM, only a few projects have used it to deliver improved management outcomes [4.Westgate M.J. et al.Adaptive management of biological systems: a review.Biol. Conserv. 2013; 158: 128-139Crossref Scopus (259) Google Scholar,15.Richardson S. et al.A systematic review of adaptive wildlife management for the control of invasive, non-native mammals, and other human–wildlife conflicts.Mamm. Rev. 2020; 50: 147-156Crossref Scopus (24) Google Scholar]. The literature proposes that the lack of successful examples may have several and interacting causes [4.Westgate M.J. et al.Adaptive management of biological systems: a review.Biol. Conserv. 2013; 158: 128-139Crossref Scopus (259) Google Scholar,16.Gillson L. et al.Finding common ground between adaptive management and evidence-based approaches to biodiversity conservation.Trends Ecol. Evol. 2019; 34: 31-44Abstract Full Text Full Text PDF PubMed Scopus (48) Google Scholar]: for example, complexity in terms of ecological processes and administrative levels when AM is carried out over large spatial scales [17.Cash D.W. et al.Scale and cross-scale dynamics: governance and information in a multilevel world.Ecol. Soc. 2006; 11: 1-12Crossref Google Scholar]. Moreover, as AM is conducted as part of a social–ecological system, its implementation in many instances depends on transdisciplinary and multi-actor understanding. Current global megatrends – including climate change, overexploitation of natural resources, and environmental degradation [18.IPBES Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. IPBES secretariat, Bonn, Germany2019Google Scholar, 19.Fox A.D. Madsen J. Threatened species to super-abundance: the unexpected international implications of successful goose conservation.Ambio. 2017; 46: 179-187Crossref PubMed Scopus (103) Google Scholar, 20.Meek C.L. et al.Adaptive governance and the human dimensions of marine mammal management: implications for policy in a changing North.Mar. Policy. 2011; 35: 466-476Crossref Scopus (28) Google Scholar, 21.Walther G.R. Community and ecosystem responses to recent climate change.Philos. Trans. R. Soc. B Biol. Sci. 2010; 365: 2019-2024Crossref PubMed Scopus (869) Google Scholar] – cause additional challenges for AM, as its stepwise learning approach may be too slow to keep pace with the effects of these changes [22.Cammen K.M. et al.Predator recovery, shifting baselines, and the adaptive management challenges they create.Ecosphere. 2019; 10e02579https://doi.org/10.1002/ecs2.2579Crossref Scopus (15) Google Scholar]. Wildlife populations may change quickly and profoundly, from rarity to abundance and vice versa. For example, several successful conservation interventions have drastically changed the status of red-listed mammals and birds to full recovery [19.Fox A.D. Madsen J. Threatened species to super-abundance: the unexpected international implications of successful goose conservation.Ambio. 2017; 46: 179-187Crossref PubMed Scopus (103) Google Scholar,23.Apollonio M. et al.European ungulates and their management in the 21st century. Cambridge University Press, 2010Google Scholar,24.Chapron G. et al.Recovery of large carnivores in Europe's modern human-dominated landscapes.Science. 2014; 346: 1517-1519Crossref PubMed Scopus (1173) Google Scholar]. This may require a swift shift in management strategy and objectives to avoid either continued population decline in exploited species, or increased impact on ecosystems and human livelihoods by superabundant populations [22.Cammen K.M. et al.Predator recovery, shifting baselines, and the adaptive management challenges they create.Ecosphere. 2019; 10e02579https://doi.org/10.1002/ecs2.2579Crossref Scopus (15) Google Scholar,25.Tyre A.J. Michaels S. Confronting socially generated uncertainty in adaptive management.J. Environ. Manag. 2011; 92: 1365-1370Crossref PubMed Scopus (36) Google Scholar]. Such prompt decision-making and innovation require certain capacities of management systems or organisations: for example, governance systems that allow for flexibility. Several reviews of AM have identified and listed possible obstacles [4.Westgate M.J. et al.Adaptive management of biological systems: a review.Biol. Conserv. 2013; 158: 128-139Crossref Scopus (259) Google Scholar,26.Gregory R. et al.Deconstructing adaptive management: criteria for applications to environmental management.Ecol. Appl. 2006; 16: 2411-2425Crossref PubMed Scopus (231) Google Scholar,27.Williams B.K. Brown E.D. Double-loop learning in adaptive management: the need, the challenge, and the opportunity.Environ. Manag. 2018; 62: 995-1006Crossref PubMed Scopus (30) Google Scholar], but few if any have systematically quantified their frequency. Such quantification is valuable to highlight particularly problematic obstacles, and to be able to present solutions as part of a coherent framework. Moreover, with current megatrends, such quantification can assist putting more focus on challenges related to profoundly changing conditions and management goals. This analysis is timely, as large environmental changes are set to become more frequent in the near future. Furthermore, challenges facing AM, such as profoundly changing conditions and mega trends, are in many respects similar to obstacles facing decision-making in natural resource management, adaptive or otherwise. Lessons learnt in AM of wildlife may therefore provide valuable insights also for the management of natural resources more generally. We review the literature about AM of wildlife to systematically quantify the frequency of different categories of obstacles to the implementation of AM, with special emphasis on systems with profoundly changing scenarios and objectives (Appendix S1 in the supplemental information online). We then identify solutions to formulate recommendations on how to build capacities to improve the implementation of AM. As an illustration of how obstacles to AM can be addressed in practice, we present a case study currently engaging practitioners and policy makers, namely, the adaptive flyway management of European goose populations (Box 1).Box 1Case study: adaptive management of European geeseAM of European goose populations is an illustrative example of the complexity that wildlife practitioners currently need to handle. It involves uncertainty, conservation of declining species, harvest strategies of increasing species, and mitigation of ecosystem disservices (e.g., ecosystem impact, crop damage, air safety concerns). Goose management has recently changed profoundly from managing rare and threatened species to handling the same species when superabundant [11.Marjakangas A. et al.International Single Species Action Plan for the Conservation of the Taiga Bean Goose (Technical series No. 56), AEWA, Bonn, Germany.2015Google Scholar,19.Fox A.D. Madsen J. Threatened species to super-abundance: the unexpected international implications of successful goose conservation.Ambio. 2017; 46: 179-187Crossref PubMed Scopus (103) Google Scholar,80.Buij R. et al.Balancing ecosystem function, services and disservices resulting from expanding goose populations.Ambio. 2017; 46: 301-318Crossref PubMed Scopus (43) Google Scholar,88.Montràs-Janer T. et al.Relating national levels of crop damage to the abundance of large grazing birds: implications for management.J. Appl. Ecol. 2019; 56: 2286-2297Crossref Scopus (30) Google Scholar]. As goose species migrate across nations with different legislations, objectives, cultures, and norms [89.Bainbridge I. Goose management in Scotland: an overview.Ambio. 2017; 462: 224-230Crossref Scopus (15) Google Scholar,90.Stroud D. et al.Key actions towards the sustainable management of European geese.Ambio. 2017; 46: 328-338Crossref PubMed Scopus (23) Google Scholar], coordinating management becomes a challenge [91.Tombre I.M. et al.Towards a solution to the goose-agriculture conflict in North Norway, 1988-2012: the interplay between policy, stakeholder influence and goose population dynamics.PLoS One. 2013; 8e71912https://doi.org/10.1371/journal.poneCrossref PubMed Scopus (38) Google Scholar,92.Eriksson L. et al.The public and geese: a conflict on the rise?.Hum. Dimens. Wildl. 2020; 25: 421-437Crossref Scopus (14) Google Scholar].To cope with these challenges, the secretariat of the African–Eurasian Migratory Waterbird Agreement (https://www.unep-aewa.org/) approached countries sharing migratory goose species. Important parts of the proposed AM were to create forums and discussion groups to enable communication, consensus-building, and engagement among stakeholders, and to form platforms where national delegations (authorities, scientific experts, and interest groups) meet for decisions and information sharing (Figure I). Goose management meetings are now arranged annually, and several task force groups continuously work with issues related to crop damage and species-specific questions related to population conservation and control (e.g., data collection). Practitioners are supported by scientists via a data platform (collecting and compiling data) and a modelling consortium (providing predictive population models). Using this structure, several international goose management plans have been launched [11.Marjakangas A. et al.International Single Species Action Plan for the Conservation of the Taiga Bean Goose (Technical series No. 56), AEWA, Bonn, Germany.2015Google Scholar,12.Madsen J. et al.Implementation of the first adaptive management plan for a European migratory waterbird population: the case of the Svalbard pink-footed goose Anser brachyrhynchus.Ambio. 2017; 462: 275-289Crossref Scopus (68) Google Scholar,93.Powolny T. et al.AEWA International Single Species Management Plan for the Greylag Goose (Anser anser) AEWA Technical Series No. 71. Bonn, Germany.2018Google Scholar,94.Jensen G.H. et al.AEWA International Single Species Management Plan for the Barnacle Goose - Russia/Germany & Netherlands population, East Greenland/Scotland & Ireland population, Svalbard/South-west Scotland population. AEWA Technical Series No. 70. Bonn, Germany.2018Google Scholar], all striving for viable populations while minimising 'ecosystem disservices' [95.Lefebvre J. et al.The greater snow goose Anser caerulescens atlanticus: managing an overabundant population.Ambio. 2017; 46: 262-274Crossref PubMed Scopus (30) Google Scholar]. The management plans are based on predictive population models, coordinated monitoring, and common hunting quotas [11.Marjakangas A. et al.International Single Species Action Plan for the Conservation of the Taiga Bean Goose (Technical series No. 56), AEWA, Bonn, Germany.2015Google Scholar,12.Madsen J. et al.Implementation of the first adaptive management plan for a European migratory waterbird population: the case of the Svalbard pink-footed goose Anser brachyrhynchus.Ambio. 2017; 462: 275-289Crossref Scopus (68) Google Scholar]. One of the plans (pink-footed goose, Anser brachyrhynchus) has been implemented and the population size is now approaching the set goal [12.Madsen J. et al.Implementation of the first adaptive management plan for a European migratory waterbird population: the case of the Svalbard pink-footed goose Anser brachyrhynchus.Ambio. 2017; 462: 275-289Crossref Scopus (68) Google Scholar]. Yet, implementation requires that actors at the local level support nationally agreed goals and actively contribute to achieving them [96.Tombre I.M. et al.Population control by means of organised hunting effort: experiences from a voluntary goose hunting arrangement.Ambio. 2022; 51: 728-742Crossref PubMed Scopus (4) Google Scholar]. This suggests a further need for capacity-building within countries, particularly at the regional and local levels.The goose management platform is a good example of how to strengthen capacities to handle obstacles to AM. However, some obstacles remain, one of which can be illustrated by the successful legal protection of the barnacle goose (Branta leucopsis) (Figure II), which has permitted the species to become superabundant [19.Fox A.D. Madsen J. Threatened species to super-abundance: the unexpected international implications of successful goose conservation.Ambio. 2017; 46: 179-187Crossref PubMed Scopus (103) Google Scholar,93.Powolny T. et al.AEWA International Single Species Management Plan for the Greylag Goose (Anser anser) AEWA Technical Series No. 71. Bonn, Germany.2018Google Scholar]. At present, this protection makes it impossible to set goals to reduce the barnacle goose population, the most abundant goose species in Europe, while hunting remains open for much less common species [12.Madsen J. et al.Implementation of the first adaptive management plan for a European migratory waterbird population: the case of the Svalbard pink-footed goose Anser brachyrhynchus.Ambio. 2017; 462: 275-289Crossref Scopus (68) Google Scholar,93.Powolny T. et al.AEWA International Single Species Management Plan for the Greylag Goose (Anser anser) AEWA Technical Series No. 71. Bonn, Germany.2018Google Scholar]. Thus, the legislative precautionary AM approach to rescue critically small goose populations may sometimes need to shift focus in order to prevent possible irreversible 'ecosystem disservices'. Such shifts will require changes inside and outside of the AM process (i.e., in legislation and institutional structure) [20.Meek C.L. et al.Adaptive governance and the human dimensions of marine mammal management: implications for policy in a changing North.Mar. Policy. 2011; 35: 466-476Crossref Scopus (28) Google Scholar,25.Tyre A.J. Michaels S. Confronting socially generated uncertainty in adaptive management.J. Environ. Manag. 2011; 92: 1365-1370Crossref PubMed Scopus (36) Google Scholar].Figure IIThe barnacle goose (Branta leucopsis) is an example of a species that has shown a profound population change, going from threatened to superabundant over 3–4 decades, causing challenges to adaptive management (AM).View Large Image Figure ViewerDownload Hi-res image Download (PPT) AM of European goose populations is an illustrative example of the complexity that wildlife practitioners currently need to handle. It involves uncertainty, conservation of declining species, harvest strategies of increasing species, and mitigation of ecosystem disservices (e.g., ecosystem impact, crop damage, air safety concerns). Goose management has recently changed profoundly from managing rare and threatened species to handling the same species when superabundant [11.Marjakangas A. et al.International Single Species Action Plan for the Conservation of the Taiga Bean Goose (Technical series No. 56), AEWA, Bonn, Germany.2015Google Scholar,19.Fox A.D. Madsen J. Threatened species to super-abundance: the unexpected international implications of successful goose conservation.Ambio. 2017; 46: 179-187Crossref PubMed Scopus (103) Google Scholar,80.Buij R. et al.Balancing ecosystem function, services and disservices resulting from expanding goose populations.Ambio. 2017; 46: 301-318Crossref PubMed Scopus (43) Google Scholar,88.Montràs-Janer T. et al.Relating national levels of crop damage to the abundance of large grazing birds: implications for management.J. Appl. Ecol. 2019; 56: 2286-2297Crossref Scopus (30) Google Scholar]. As goose species migrate across nations with different legislations, objectives, cultures, and norms [89.Bainbridge I. Goose management in Scotland: an overview.Ambio. 2017; 462: 224-230Crossref Scopus (15) Google Scholar,90.Stroud D. et al.Key actions towards the sustainable management of European geese.Ambio. 2017; 46: 328-338Crossref PubMed Scopus (23) Google Scholar], coordinating management becomes a challenge [91.Tombre I.M. et al.Towards a solution to the goose-agriculture conflict in North Norway, 1988-2012: the interplay between policy, stakeholder influence and goose population dynamics.PLoS One. 2013; 8e71912https://doi.org/10.1371/journal.poneCrossref PubMed Scopus (38) Google Scholar,92.Eriksson L. et al.The public and geese: a conflict on the rise?.Hum. Dimens. Wildl. 2020; 25: 421-437Crossref Scopus (14) Google Scholar]. To cope with these challenges, the secretariat of the African–Eurasian Migratory Waterbird Agreement (https://www.unep-aewa.org/) approached countries sharing migratory goose species. Important parts of the proposed AM were to create forums and discussion groups to enable communication, consensus-building, and engagement among stakeholders, and to form platforms where national delegations (authorities, scientific experts, and interest groups) meet for decisions and information sharing (Figure I). Goose management meetings are now arranged annually, and several task force groups continuously work with issues related to crop damage and species-specific questions related to population conservation and control (e.g., data collection). Practitioners are supported by scientists via a data platform (collecting and compiling data) and a modelling consortium (providing predictive population models). Using this structure, several international goose management plans have been launched [11.Marjakangas A. et al.International Single Species Action Plan for the Conservation of the Taiga Bean Goose (Technical series No. 56), AEWA, Bonn, Germany.2015Google Scholar,12.Madsen J. et al.Implementation of the first adaptive management plan for a European migratory waterbird population: the case of the Svalbard pink-footed goose Anser brachyrhynchus.Ambio. 2017; 462: 275-289Crossref Scopus (68) Google Scholar,93.Powolny T. et al.AEWA International Single Species Management Plan for the Greylag Goose (Anser anser) AEWA Technical Series No. 71. Bonn, Germany.2018Google Scholar,94.Jensen G.H. et al.AEWA International Single Species Management Plan for the Barnacle Goose - Russia/Germany & Netherlands population, East Greenland/Scotland & Ireland population, Svalbard/South-west Scotland population. AEWA Technical Series No. 70. Bonn, Germany.2018Google Scholar], all striving for viable populations while minimising 'ecosystem disservices' [95.Lefebvre J. et al.The greater snow goose Anser caerulescens atlanticus: managing an overabundant population.Ambio. 2017; 46: 262-274Crossref PubMed Scopus (30) Google Scholar]. The management plans are based on predictive population models, coordinated monitoring, and common hunting quotas [11.Marjakangas A. et al.International Single Species Action Plan for the Conservation of the Taiga Bean Goose (Technical series No. 56), AEWA, Bonn, Germany.2015Google Scholar,12.Madsen J. et al.Implementation of the first adaptive management plan for a European migratory waterbird population: the case of the Svalbard pink-footed goose Anser brachyrhynchus.Ambio. 2017; 462: 275-289Crossref Scopus (68) Google Scholar]. One of the plans (pink-footed goose, Anser brachyrhynchus) has been implemented and the population size is now approaching the set goal [12.Madsen J. et al.Implementation of the first adaptive management plan for a European migratory waterbird population: the case of the Svalbard pink-footed goose Anser brachyrhynchus.Ambio. 2017; 462: 275-289Crossref Scopus (68) Google Scholar]. Yet, implementation requires that actors at the local level support nationally agreed goals and actively contribute to achieving them [96.Tombre I.M. et al.Population control by means of organised hunting effort: experiences from a voluntary goose hunting arrangement.Ambio. 2022; 51: 728-742Crossref PubMed Scopus (4) Google Scholar]. This suggests a further need for capacity-building within countries, particularly at the regional and local levels. The goose management platform is a good example of how to strengthen capacities to handle obstacles to AM. However, some obstacles remain, one of which can be illustrated by the successful legal protection of the barnacle goose (Branta leucopsis) (Figure II), which has permitted the species to become superabundant [19.Fox A.D. Madsen J. Threatened species to super-abundance: the unexpected international implications of successful goose conservation.Ambio. 2017; 46: 179-187Crossref PubMed Scopus (103) Google Scholar,93.Powolny T. et al.AEWA International Single Species Management Plan for the Greylag Goose (Anser anser) AEWA Technical Series No. 71. Bonn, Germany.2018Google Scholar]. At present, this protection makes it impossible to set goals to reduce the barnacle goose population, the most abundant goose species in Europe, while hunting remains open for much less common species [12.Madsen J. et al.Implementation of the first adaptive management plan for a European migratory waterbird population: the case of the Svalbard pink-footed goose Anser brachyrhynchus.Ambio. 2017; 462: 275-289Crossref Scopus (68) Google Scholar,93.Powolny T. et al.AEWA International Single Species Management Plan for the Greylag Goose (Anser anser) AEWA Technical Series No. 71. Bonn, Germany.2018Google Scholar]. Thus, the legislative precautionary AM approach to rescue critically small goose populations may sometimes need to shift focus in order to prevent possible irreversible 'ecosystem disservices'. Such shifts will require changes inside and outside of the AM process (i.e., in legislation and institutional structure) [20.Meek C.L. et al.Adaptive governance and the human dimensions of marine mammal management: implications for policy in a changing North.Mar. Policy. 2011; 35: 466-476Crossref Scopus (28) Google Scholar,25.Tyre A.J. Michaels S. Confronting socially generated uncertainty in adaptive management.J. Environ. Manag. 2011; 92: 1365-1370Crossref PubMed Scopus (36) Google Scholar]. We identified three main categories of obstacles related to: (i) the 'AM process' per se (e.g., lack of resources, inadequate actor involvement, or shortcomings in operational processes), (ii) the 'ecosystem', focusing on the environment to which AM was applied, and (iii) 'governance', comprising the frame of in